A Comprehensive Literature Review of Vehicle License Plate Detection Methods

License plate (LP) detection algorithms have made considerable strides in the literature, showcasing enhanced performance in recognizing LPs from images. However, these algorithms face limitations from various environmental conditions and the diverse LP variants. Over several decades, researchers have diligently explored various approaches to LP detection. The task of detecting multiple LPs within an image while accommodating challenges like translation, scaling, rotation, and the influence of environmental and meteorological factors poses a formidable challenge, with only a select few algorithms proving effective. Efficient LP detection systems ideally mirror human perception, allowing the detection of multiple LPs within a given input image. Regrettably, most existing LP detection methods documented in the literature exhibit specificity towards particular vehicles or countries and perform optimally only under controlled conditions. This review paper systematically categorizes the LP detection methods found in the literature based on the techniques they employ for LP detection. It examines and analyzes their respective methodologies, strengths, and weaknesses. This comprehensive analysis aims to provide valuable insights for LP detection and recognition researchers. The ultimate goal is to inspire the development of universal LP detection methods capable of performing robustly under unconstrained real -world conditions.